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Population pharmacokinetics of nintedanib in patients with idiopathic pulmonary fibrosis.
Pulmonary Pharmacology & Therapeutics 2018 Februrary
BACKGROUND: Nintedanib is a potent intracellular inhibitor of tyrosine kinases, including the receptor kinases vascular endothelial growth factor, platelet-derived growth factor and fibroblast growth factor. A previous model assessed the population pharmacokinetics of nintedanib and its main metabolite BIBF 1202 in patients with non-small cell lung cancer and idiopathic pulmonary fibrosis (IPF). The objective of this analysis was to further characterise the population pharmacokinetics of nintedanib in patients with IPF by including data from the Phase III trials.
METHODS: We pooled data from 933 patients with IPF participating in the Phase II TOMORROW trial and the two Phase III INPULSIS trials. Plasma concentrations of nintedanib (n = 3501) were analysed using nonlinear mixed-effects modelling.
RESULTS: Pharmacokinetics of nintedanib was described by a one-compartment model with linear elimination, first-order absorption and an absorption lag time. The population estimates of absorption rate, lag time, apparent total clearance and apparent volume of distribution at steady state for a typical IPF patient were 0.0814 h-1 , 0.689 h, 994 L/h, and 265 L. The model confirmed age, body weight, smoking and Asian race (with different effect sizes in different Asian subpopulations) as statistically significant covariates influencing nintedanib exposure. Serum lactate dehydrogenase levels were identified as another factor significantly influencing nintedanib plasma concentrations. No individual covariate at extreme values (5th and 95th percentiles of baseline for continuous covariates) resulted in changes in exposure of more than 50% relative to a typical patient.
CONCLUSIONS: The developed model provides further details about the pharmacokinetics of nintedanib in patients with IPF and can be used for simulations exploring covariate effects and exposure-response analyses in this patient population.
METHODS: We pooled data from 933 patients with IPF participating in the Phase II TOMORROW trial and the two Phase III INPULSIS trials. Plasma concentrations of nintedanib (n = 3501) were analysed using nonlinear mixed-effects modelling.
RESULTS: Pharmacokinetics of nintedanib was described by a one-compartment model with linear elimination, first-order absorption and an absorption lag time. The population estimates of absorption rate, lag time, apparent total clearance and apparent volume of distribution at steady state for a typical IPF patient were 0.0814 h-1 , 0.689 h, 994 L/h, and 265 L. The model confirmed age, body weight, smoking and Asian race (with different effect sizes in different Asian subpopulations) as statistically significant covariates influencing nintedanib exposure. Serum lactate dehydrogenase levels were identified as another factor significantly influencing nintedanib plasma concentrations. No individual covariate at extreme values (5th and 95th percentiles of baseline for continuous covariates) resulted in changes in exposure of more than 50% relative to a typical patient.
CONCLUSIONS: The developed model provides further details about the pharmacokinetics of nintedanib in patients with IPF and can be used for simulations exploring covariate effects and exposure-response analyses in this patient population.
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